config_stp_wcc

Space Telescope Pathfinder's WCC-specific repository for support data and configuration management as an installable python package

Details on the change control process are found in the coronograph design documentation repository

The parameters for each subsystem are found in the configs directory, and supporting data is found in the support_data directory. A description of how configurations are used in UASAL software, users can find an example notebook in the docs directory of the config_project_template repository.

Dependencies and Requirements

config_stp_wcc is dependent on utils_config but will automatically be installed via

pip install "git+https://github.com/uasal/utils_config.git@develop"

ssh keys are necessary for the pip-based install. Verify you have ssh keys installed in GitHub, or check out this ssh key tutorial

Pip Installation

pip install git+ssh://git@github.com/uasal/config_stp_wcc.git

Git Clone Installation

1. Clone the Repository

git clone git@github.com:uasal/config_stp_wcc.git
cd config_stp_wcc

2. Install the Package

pip install .

Usage

config_stp_wcc makes usage of the ConfigLoader class (as config_loader) from utils_config via the load_config_values method, accepting 'raw' 'parsed' or 'unitless' as an argument, returning a dictionary after parsing the 'configs' directory for .toml filies

import config_stp_wcc
data = config_stp_wcc.load_config_values()

load_config_values() has a default argument of 'raw' but alternatively accepts 3 arguments that trigger data to be formatted differently:

• load_config_values('unitless') -> 0.01
• load_config_values('parsed') -> {'value': 0.01, 'unit': 'arcsecond'}
• load_config_values('raw') -> 10e-3arcsecond

For importing data and keeping code consistent across installs, config_stp_wcc will return the path to support_data with get_data_path()

import config_stp_wcc
data_path = config_stp_wcc.get_data_path()
print(data_path)

Astropy Unit Validation

All .toml config values should have a valid astropy unit if any units are defined. If no unit is included, the value is assumed to be unitless. A GitHub CI will automatically run a test on push to validate astropy units in the configs, reporting any issues with non-conforming astropy units. If you'd like to perform validation locally, you may run pytest tests/test_configs.py from the root directory of the repo. Alternatively in your python environment you may run the following snippit:

import config_stp_wcc
config_stp_wcc.load_config_values("parsed", return_loader=True).validate_astropy()

Which will return 'True' if every unit is a valid astropy unit, or a list containing every invalid unit. If you would like to use a custom u nit, click here for how to define that as a custom unit in Astropy.

Git large file storage (LFS)

This repository makes use of the git large file storage for files listed in the .gitattributes file. Accessing these files will require users having (Git Large File Storage (LFS))[https://docs.github.com/en/repositories/working-with-files/managing-large-files/installing-git-large-file-storage] installed on their local machine.

If you have Git LFS installed, then the large files will be pulled by default. This can be disabled in your gitconfig, as described (at this link)[https://stackoverflow.com/questions/42019529/how-to-clone-pull-a-git-repository-ignoring-lfs].